Difference between revisions of "RecSys 2017"

From OPENRESEARCH fixed Wiki
Jump to navigation Jump to search
(modified through wikirestore by Th)
(modified through wikirestore by orapi)
 
(3 intermediate revisions by the same user not shown)
Line 8: Line 8:
 
|Accepted short papers=20
 
|Accepted short papers=20
 
|Acronym          =RecSys 2017
 
|Acronym          =RecSys 2017
|End date        =2017/08/31
+
|End date        =2017-08-31
 
|Series          =RecSys
 
|Series          =RecSys
 
|Type            =Conference
 
|Type            =Conference
Line 14: Line 14:
 
|State            =IT/25
 
|State            =IT/25
 
|City            =IT/25/Como
 
|City            =IT/25/Como
 +
|Year            =2017
 
|Homepage        =https://recsys.acm.org/recsys17/
 
|Homepage        =https://recsys.acm.org/recsys17/
|Start date      =2017/08/27
+
|Start date      =2017-08-27
 
|Title            =11th ACM Conference on Recommender Systems
 
|Title            =11th ACM Conference on Recommender Systems
 
|Accepted papers  =26
 
|Accepted papers  =26
|Submitted papers =125}}
+
|Submitted papers =125
 +
}}
 
Topics of interest for RecSys 2017 include (but are not limited to):
 
Topics of interest for RecSys 2017 include (but are not limited to):
 
   
 
   

Latest revision as of 03:45, 6 December 2021


Event Rating

median worst
Pain1.svg Pain5.svg

List of all ratings can be found at RecSys 2017/rating

RecSys 2017
11th ACM Conference on Recommender Systems
Event in series RecSys
Dates 2017-08-27 (iCal) - 2017-08-31
Homepage: https://recsys.acm.org/recsys17/
Location
Location: IT/25/Como, IT/25, IT
Loading map...

Important dates
Abstracts: 2017/03/27
Papers: 2017/04/03
Submissions: 2017/04/03
Camera ready due: 2017/07/07
Accepted short papers: 20
Papers: Submitted 125 / Accepted 26 (20.8 %)
Committees
General chairs: Paolo Cremonesi, Francesco Ricci
PC chairs: Alexander Tuzhilin, Shlomo Berkovsky
Table of Contents

Topics of interest for RecSys 2017 include (but are not limited to):

  • Algorithm scalability
  • Case studies of real-world implementations
  • Conversational recommender systems
  • Context-aware recommenders
  • Evaluation metrics and studies
  • Explanations and evidence
  • Field and user studies
  • Group recommenders
  • Innovative/New applications
  • Machine learning for recommendation
  • Mobile and multi-channel recommendations
  • Novel paradigms
  • Personalisation
  • Preference elicitation
  • Privacy and Security
  • Recommendation algorithms
  • Social recommenders
  • Semantic technologies for recommendation
  • Trust and reputation
  • Theoretical foundations
  • User interaction and interfaces
  • User modelling